b'Zhe Li'

research

∙ 03/11/2021

Temporal Action Segmentation from Timestamp Supervision

Temporal action segmentation approaches have been very successful recent...

0 Zhe Li, et al. ∙

research

∙ 11/01/2020

On the Distribution of SINR for MIMO Systems with Widely Linear MMSE Receivers

The widely linear least mean square error (WLMMSE) receiver has been an ...

0 Wei Deng, et al. ∙

research

∙ 09/24/2020

Distributed Community Detection for Large Scale Networks Using Stochastic Block Model

With rapid developments of information and technology, large scale netwo...

0 Shihao Wu, et al. ∙

research

∙ 08/10/2020

A Full Second-Order Analysis of the Widely Linear MVDR Beamformer for Noncircular Signals

A full performance analysis of the widely linear (WL) minimum variance d...

0 Zhe Li, et al. ∙

research

∙ 07/20/2020

Improving Attention-Based Handwritten Mathematical Expression Recognition with Scale Augmentation and Drop Attention

Handwritten mathematical expression recognition (HMER) is an important r...

0 Zhe Li, et al. ∙

research

∙ 05/18/2020

Joint Multi-Dimension Pruning

We present joint multi-dimension pruning (named as JointPruning), a new ...

6 Zechun Liu, et al. ∙

research

∙ 04/06/2020

Robust 3D Self-portraits in Seconds

In this paper, we propose an efficient method for robust 3D self-portrai...

8 Zhe Li, et al. ∙

research

∙ 03/18/2020

PolyFit: Polynomial-based Indexing Approach for Fast Approximate Range Aggregate Queries

Range aggregate queries find frequent application in data analytics. In ...

0 Zhe Li, et al. ∙

research

∙ 03/07/2020

RCC-Dual-GAN: An Efficient Approach for Outlier Detection with Few Identified Anomalies

Outlier detection is an important task in data mining and many technolog...

11 Zhe Li, et al. ∙

research

∙ 03/02/2020

Long Short-Term Sample Distillation

In the past decade, there has been substantial progress at training incr...

5 Liang Jiang, et al. ∙

research

∙ 11/11/2019

Learning From Brains How to Regularize Machines

Despite impressive performance on numerous visual tasks, Convolutional N...

36 Zhe Li, et al. ∙

research

∙ 04/12/2019

Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation

Accurate multi-organ abdominal CT segmentation is essential to many clin...

0 Yuyin Zhou, et al. ∙

research

∙ 02/28/2019

CircConv: A Structured Convolution with Low Complexity

Deep neural networks (DNNs), especially deep convolutional neural networ...

0 Siyu Liao, et al. ∙

research

∙ 12/12/2018

E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs

Recurrent Neural Networks (RNNs) are becoming increasingly important for...

0 Zhe Li, et al. ∙

research

∙ 09/28/2018

Generative Adversarial Active Learning for Unsupervised Outlier Detection

Outlier detection is an important topic in machine learning and has been...

18 Yezheng Liu, et al. ∙

research

∙ 08/30/2018

A Unified Analysis of Stochastic Momentum Methods for Deep Learning

Stochastic momentum methods have been widely adopted in training deep ne...

0 Yan Yan, et al. ∙

research

∙ 06/05/2018

EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching

Designing the structure of neural networks is considered one of the most...

0 Jian Ren, et al. ∙

research

∙ 06/03/2018

An Aggressive Genetic Programming Approach for Searching Neural Network Structure Under Computational Constraints

Recently, there emerged revived interests of designing automatic program...

0 Zhe Li, et al. ∙

research

∙ 05/10/2018

Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing

Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendo...

0 Zhe Li, et al. ∙

research

∙ 04/11/2018

Learning Topics using Semantic Locality

The topic modeling discovers the latent topic probability of the given t...

0 Ziyi Zhao, et al. ∙

research

∙ 03/20/2018

Efficient Recurrent Neural Networks using Structured Matrices in FPGAs

Recurrent Neural Networks (RNNs) are becoming increasingly important for...

0 Zhe Li, et al. ∙

research

∙ 03/20/2018

C3PO: Database and Benchmark for Early-stage Malicious Activity Detection in 3D Printing

Increasing malicious users have sought practices to leverage 3D printing...

0 Zhe Li, et al. ∙

research

∙ 03/14/2018

C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs

Recently, significant accuracy improvement has been achieved for acousti...

0 Shuo Wang, et al. ∙

research

∙ 02/25/2018

A Framework in CRM Customer Lifecycle: Identify Downward Trend and Potential Issues Detection

Customer retention is one of the primary goals in the area of customer r...

0 Kun Hu, et al. ∙

research

∙ 02/18/2018

Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework

Hardware accelerations of deep learning systems have been extensively in...

0 Yanzhi Wang, et al. ∙

research

∙ 02/15/2018

Image Dataset for Visual Objects Classification in 3D Printing

The rapid development in additive manufacturing (AM), also known as 3D p...

0 Hongjia Li, et al. ∙

research

∙ 02/03/2018

An Area and Energy Efficient Design of Domain-Wall Memory-Based Deep Convolutional Neural Networks using Stochastic Computing

With recent trend of wearable devices and Internet of Things (IoTs), it ...

0 Xiaolong Ma, et al. ∙

research

∙ 11/22/2017

Evaluate the Malignancy of Pulmonary Nodules Using the 3D Deep Leaky Noisy-or Network

Automatic diagnosing lung cancer from Computed Tomography (CT) scans inv...

0 Fangzhou Liao, et al. ∙

research

∙ 11/17/2017

Thoracic Disease Identification and Localization with Limited Supervision

Accurate identification and localization of abnormalities from radiology...

0 Zhe Li, et al. ∙

research

∙ 09/09/2017

A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer

In this paper, we present a simple analysis of fast rates with high pr...

0 Tianbao Yang, et al. ∙

research

∙ 08/29/2017

CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices

Large-scale deep neural networks (DNNs) are both compute and memory inte...

0 Caiwen Ding, et al. ∙

research

∙ 06/13/2017

SEP-Nets: Small and Effective Pattern Networks

While going deeper has been witnessed to improve the performance of conv...

0 Zhe Li, et al. ∙

research

∙ 03/12/2017

Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks

Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecede...

0 Ji Li, et al. ∙

research

∙ 03/01/2017

Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank

Recently low displacement rank (LDR) matrices, or so-called structured m...

0 Liang Zhao, et al. ∙

research

∙ 11/18/2016

SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing

With recent advancing of Internet of Things (IoTs), it becomes very attr...

0 Ao Ren, et al. ∙

research

∙ 04/12/2016

Unified Convergence Analysis of Stochastic Momentum Methods for Convex and Non-convex Optimization

Recently, stochastic momentum methods have been widely adopted in train...

0 Tianbao Yang, et al. ∙

research

∙ 02/06/2016

Improved Dropout for Shallow and Deep Learning

Dropout has been witnessed with great success in training deep neural ne...

0 Zhe Li, et al. ∙

Zhe Li

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